Myeloid differentiation factor-2/LY96, a potential predictive biomarker of metastasis and poor outcomes in prostate cancer: clinical implications as a potential therapeutic target.
Marina G FerrariAlexis P Jimenez-UribeLi WangLuke H HoeppnerPaari MuruganEunsil HahmJindan YuTimothy M KuzelSergio A GradiloneAdrian P MansiniPublished in: Oncogene (2023)
Prostate cancer (CaP) is the most diagnosed cancer in males and the second leading cause of cancer deaths. Patients with localized tumors are generally curable. However, no curative treatment exists for patients with advanced and metastatic disease. Therefore, identifying critical proteins involved in the metastatic process would help to develop new therapeutic options for patients with advanced and aggressive CaP. We provide strong evidence that Myeloid differentiation factor-2 (MD2) plays a critical role in metastasis and CaP progression. Analysis of tumor genomic data showed that amplifications of MD2 and increased expression are associated with poor outcomes in patients. Immunohistochemistry analysis of tumor tissues showed a correlation between the expression of MD2 and cancer progression. The Decipher-genomic test validated the potential of MD2 in predicting metastasis. In vitro studies demonstrated that MD2 confers invasiveness by activating MAPK and NF-kB signaling pathways and inducing epithelial-mesenchymal transition. Furthermore, we show that metastatic cells release MD2 (sMD2). We measured serum-sMD2 in patients and found that the level is correlated to disease extent. We determined the significance of MD2 in metastasis in vivo and as a therapeutic target, showing that the molecular and pharmacological targeting of MD2 significantly inhibited metastasis in murine models. We conclude that MD2 predicts metastatic behavior, and serum-MD2 could be studied as a potential non-invasive biomarker for metastasis, whereas MD2 presence on prostate biopsy predicts adverse disease outcome. We suggest MD2-targeted therapies could be developed as potential treatments for aggressive metastatic disease.
Keyphrases
- molecular dynamics
- prostate cancer
- signaling pathway
- small cell lung cancer
- squamous cell carcinoma
- epithelial mesenchymal transition
- papillary thyroid
- poor prognosis
- end stage renal disease
- ejection fraction
- oxidative stress
- emergency department
- type diabetes
- prognostic factors
- human health
- acute myeloid leukemia
- young adults
- gene expression
- pi k akt
- risk assessment
- machine learning
- long non coding rna
- inflammatory response
- dna methylation
- adipose tissue
- dendritic cells
- artificial intelligence
- copy number
- electronic health record
- deep learning
- peritoneal dialysis
- big data
- binding protein
- lps induced
- childhood cancer
- single molecule
- data analysis
- smoking cessation